Abstract
Abstract: Analyzing the past data and planning for future is very important for every public and private organizational decisions. Now a days individuals also using forecasting methods to invest in Stock market. Investments in mutual funds and in registered companies in companies in stock market is the order of the day. In this paper, advanced forecasting methods are fitted to the time related stock price data to study its effectiveness in forecasting future events. Auto correlation and standard models have been analyzed before fitting this model to the above data. The forecasting can be done by using the ARIMA time series(using auto. arima) model. A particular reference have been made to Box and Jenkins approach for day to day stock price data values of Exxon Mobile Corporation from '1995-01-01 to 2020-03-01. With usual statistical software R. Here, ARIMA(1,1,1,) is fitted to this data, These results are compared with the model ARIMA(1,1,1,) by using accuracy measures. Keywords: ARIMA: Auto Regressive Integrated Moving Average ACF: Auto Correlation Function PACF: Partial Auto Correlation Function AIC: Akaikae Information Criterion RMSE: Root mean square error XOM: Exxon Mobil Corporation
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